Linear Algebra Exercises-n-Answers.pdf
Linear Algebra Exercises-n-Answers.pdf
Linear Algebra Exercises-n-Answers.pdf
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140 <strong>Linear</strong> <strong>Algebra</strong>, by Hefferon<br />
and so (as in Example 3.5 and 3.6, we can just find the vectors perpendicular to all of the members<br />
of the basis)<br />
( ) ( ) (<br />
M ⊥ u ∣∣ 1 ∣∣ 1<br />
= { −1 · u + 1 · v = 0} = {k · k ∈ R} B<br />
v<br />
1<br />
M ⊥ = 〈 〉<br />
1)<br />
and representing the vector with respect<br />
(<br />
to the concatenation<br />
( ) (<br />
gives this.<br />
1 −1 1<br />
= −2 · − 1 ·<br />
−3)<br />
1 1)<br />
Keeping the M part yields the answer.<br />
( (<br />
1 2<br />
proj M,M ⊥( ) =<br />
−3)<br />
−2)<br />
The third part is also a simple calculation (there is a 1×1 matrix in the middle, and the inverse<br />
of it is also 1×1)<br />
A ( A trans A ) ( ) (<br />
−1<br />
A trans −1 (−1 ) ( )) −1 ( )<br />
−1 ( ) −1 (2 ) −1 ( )<br />
=<br />
1 −1 1 = −1 1<br />
1<br />
1<br />
1<br />
( ) ( ) ( )<br />
−1 (1/2 ) ( ) −1 (−1/2 ) 1/2 −1/2<br />
=<br />
−1 1 = 1/2 =<br />
1<br />
1<br />
−1/2 1/2<br />
which of course gives the same answer.<br />
( ( ) ( (<br />
1 1/2 −1/2 1 2<br />
proj M ( ) =<br />
=<br />
−3)<br />
−1/2 1/2 −3)<br />
−2)<br />
(b) Paramatrization gives this.<br />
⎛<br />
M = {c · ⎝ −1 ⎞<br />
0 ⎠ ∣ c ∈ R}<br />
1<br />
With that, the formula for<br />
⎛<br />
the first way gives this.<br />
⎝ 0 ⎞ ⎛<br />
1⎠<br />
⎝ −1<br />
⎞<br />
0 ⎠ ⎛<br />
2 1<br />
⎛<br />
⎝ −1<br />
⎞ ⎛<br />
0 ⎠ ⎝ −1<br />
⎞ · ⎝ −1<br />
⎞ ⎛<br />
0 ⎠ = 2 2 · ⎝ −1<br />
⎞ ⎛<br />
0 ⎠ = ⎝ −1<br />
⎞<br />
0 ⎠<br />
1<br />
1 1<br />
0 ⎠<br />
1 1<br />
To proceed by the second method<br />
⎛ ⎞<br />
we find M ⊥ ,<br />
⎛ ⎞ ⎛ ⎞<br />
M ⊥ = { ⎝ u v ⎠ ∣ −u + w = 0} = {j · ⎝ 1 0⎠ + k · ⎝ 0 1⎠ ∣ j, k ∈ R}<br />
w<br />
1 0<br />
find the representation of the given vector with respect to the concatenation of the bases B M and<br />
B M ⊥<br />
⎛<br />
⎝ 0 ⎞ ⎛<br />
1⎠ = 1 · ⎝ −1<br />
⎞ ⎛<br />
0 ⎠ + 1 · ⎝ 1 ⎞ ⎛<br />
0⎠ + 1 · ⎝ 0 ⎞<br />
1⎠<br />
2 1 1 0<br />
and retain only the M part.<br />
⎛<br />
proj M ( ⎝ 0 ⎞ ⎛<br />
1⎠) = 1 · ⎝ −1<br />
⎞ ⎛<br />
0 ⎠ = ⎝ −1<br />
⎞<br />
0 ⎠<br />
2<br />
1 1<br />
Finally, for the third method, the matrix calculation<br />
⎛ ⎞<br />
⎛ ⎞<br />
⎛ ⎞<br />
A ( A trans A ) −1<br />
−1<br />
A trans = ⎝ 0 ⎠ (( −1 0 1 ) −1<br />
⎝ 0 ⎠ ) −1 ( )<br />
−1<br />
−1 0 1 = ⎝ 0 ⎠ ( 2 ) −1 ( )<br />
−1 0 1<br />
1<br />
1<br />
1<br />
⎛<br />
= ⎝ −1 ⎞<br />
⎛<br />
0 ⎠ ( 1/2 ) ( −1 0 1 ) = ⎝ −1 ⎞<br />
⎛<br />
⎞<br />
0 ⎠ ( −1/2 0 1/2 ) 1/2 0 −1/2<br />
= ⎝ 0 0 0 ⎠<br />
1<br />
1<br />
−1/2 0 1/2<br />
followed by matrix-vector multiplication<br />
⎛<br />
proj M ( ⎝ 0 ⎞ ⎛<br />
⎞ ⎛<br />
1/2 0 −1/2<br />
1⎠)<br />
⎝ 0 0 0 ⎠ ⎝ 0 ⎞ ⎛<br />
1⎠ = ⎝ −1 ⎞<br />
0 ⎠<br />
2 −1/2 0 1/2 2 1<br />
gives the answer.